I am a PhD candidate in Sociology at Yale University, with degree expected May 2020. My research and teaching interests center on economic and political sociology with strong interests in inequality, social movements, and social networks. My research relies on qualitative methods such as in-depth interviews and fieldwork, and computational methods including social network analysis, automated text analysis, and agent-based modeling.
In my dissertation, “White-Collar Blues? The Making of the Global Middle Class in Turkey,” I explore the intertwined processes of globalization and class formation, with a particular focus on the quality of work life of elite Turkish business professionals in Istanbul and New York City. Drawing from over 100 interviews, I follow the members of this evolving stratum through the employment life course: i) selection into, ii) surviving within, and iii) opting-out of high-prestige, high-salary jobs at transnational corporations such as McKinsey, Microsoft, and Coca-Cola. My dissertation on the formation of the global middle classes builds on my experience with previous research on various boundary processes in social, economic, and political settings, including homophily in social networks, residential segregation by income, and collective identity formation in social movements. In addition to my dissertation, I am working on a project that aims to map the field of political opinion in contemporary Turkey and its change over time to illuminate the rise of authoritarianism by combining automated text analysis with social networks.
Yavas, Mustafa. 2019. “Boundary Blurring as Collective Identity Formation? The Case of the Left-wing Islamists in Turkey,” Research in Social Movements, Conflicts, and Change, 43: 109-131.
Yavas, Mustafa. 2018. “Dissecting Income Segregation: Impacts of Concentrated Affluence on Segregation of Poverty,” Journal of Mathematical Sociology, 43(1): 1-22.
Yavas, Mustafa and Gonenc Yucel. 2014. “Impact of Status Homophily on Diffusion Dynamics over Social Networks,” Social Science Computer Review, 32(3): 354-372.